DocumentCode :
2636519
Title :
Parallel imaging: some signal processing issues and solutions
Author :
Liang, Zhi-Pei ; Ying, Lei ; Xu, Dan ; Yuan, Lei
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Univ., Champaign, IL, USA
fYear :
2004
fDate :
15-18 April 2004
Firstpage :
1204
Abstract :
Parallel imaging using multiple receiver coils has emerged as an effective tool to reduce imaging time in various MRI applications. Mathematically, the imaging equation can be expressed as a weighted Fourier transform, and the image reconstruction formula can be derived from Papoulis´ generalized sampling theorem. Although perfect reconstructions can be obtained under ideal conditions, several signal processing problems exist in practical settings. This paper discusses some of these problems. Specifically, it analyzes the effect of data truncation, addresses the problem of estimating the coil sensitivity functions, and proposes a regularization scheme to cope with the ill-conditioned inverse problem associated with achieving high acceleration factors.
Keywords :
Fourier transforms; biomedical MRI; coils; image reconstruction; image sampling; inverse problems; medical image processing; MRI; Papoulis generalized sampling theorem; acceleration factors; coil sensitivity function estimation; data truncation effect; ill-conditioned inverse problem; image reconstruction formula; imaging equation; imaging time reduction; multiple receiver coils; parallel imaging; regularization scheme; signal processing; weighted Fourier transform; Acceleration; Coils; Equations; Fourier transforms; Image reconstruction; Image sampling; Inverse problems; Magnetic resonance imaging; Signal processing; Signal sampling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on
Print_ISBN :
0-7803-8388-5
Type :
conf
DOI :
10.1109/ISBI.2004.1398760
Filename :
1398760
Link To Document :
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